The activity of ion channel proteins is central to very many physiological processes, including synaptic transmission and impulse propagation in the nervous system, the control of cardiac function and vascular resistance, salt and water transport in epithelia, and the control of hormone secretion. Central to the understanding of ion channel function is the characterization of the stochastic behavior of single channels as recorded using the "patch clamp" technique. Based on this kinetic characterization, molecular details such as ligand binding rates and the rates and patterns of conformational changes can be elucidated. We propose to apply recent advances in the theory of hidden Markov models to develop improved computer algorithms for the processing of single-channel recordings. The application of this theory promises to allow meaningful kinetic information to be obtained from channels having low conductances (e.g. CFTR AND Ca++ channels) or rapid kinetics (synaptic receptors, Na+ channels) whose characterization has been hindered in the past by poor signal-to-noise ratios in the recordings. The theory also promises to greatly aid the kinetic characterization of the many neurotransmitter receptors (NMDA and other glutamate receptors; GABA, glycine) that have multiple conductance levels.